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Investigation of Physiologically Interpretable deep Neural Network Using Pulse rate Variability in Mental Fatigue recognition

Investigation of Physiologically Interpretable Deep Neural N...

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International Conference on Affective Computing and Intelligent Interaction Workshops and demos (ACIIW)

作者： Yasuhide Hyodo Kiyoshi Yoshikawa Tomoya Ikuta Yota Komoriya Human Technology R&D Department Technology Development Laboratories Sony Corporation Tokyo Japan

ISBN: (数字)9798331516451

ISBN: (纸本)9798331516468

Mental fatigue recognition by heart rate variability analysis in a photoplethysmography (PPG) device in terms of pulse rate variability (PrV) is gathering interest for stress relief and well-being applications. To realize mental fatigue recognition systems, many studies have been conducted, which showed the high accuracy of such systems evaluations. However, there are limitations in generalization due to the lack of consideration of the physiological mechanism. In this study, we developed a framework for investigating mental fatigue recognition using physiologically interpretable deep neural network (dNN) in a wrist-worn PPG device. Furthermore, we developed a novel feature extraction method that captures the temporal accumulation of arousal states to consider the perspective of cognitive resource consumption. The results suggest that the method we developed improved the mental fatigue recognition performance of the wrist-worn PPG device throughout our experiments (an accuracy of 0.90 and an F1 score of 0.91). In addition, it was observed that the method for the wrist-worn PPG device enhanced the contribution of HrV indices, known to be associated with cognitive function. The findings demonstrate that the proposed approach enhances not only accuracy but also the physiological interpretability of the model in PPG devices.

关键词： Performance evaluation Accuracy Time series analysis Artificial neural networks Human factors Fatigue Photoplethysmography Feature extraction Physiology Heart rate variability

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research on Cement Sheath Integrity Under High Temperature during In-Situ development for Shale Oil Well 28th

Research on Cement Sheath Integrity Under High Temperature D...

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28th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2022

作者： Guo, Xueli Qi, Fengzhong Yu, Yongjin Jin, Jianzhou Guo, Yuchao Ji, Hongfei Cheng, Yongqin Zhao, Zhengyang CNPC Engineering Technology R&D Company Limited Beijing China Research Institute of Petroleum Exploration and Development Beijing China China University of Petroleum Beijing China

ISBN: (纸本)9783031020964

The temperature is as high as 500 °C at the bottom of shale oil wells during in-situ development. during shale oil production, the fluids with high temperature are transmitted to the wellhead, and the wellbore temperature will rise extremely, which greatly affects the cement sheath integrity. In this paper, the linear expansion coefficient of cement stone under the temperature of 500 ℃ were measured. Based on the experimental data and the field data of shale oil well, the stage finite element modeling method was adopted to establish a casing-cement-formation (CCF) model considering the temperature and pressure coupling. The results revealed that the linear expansion coefficient of cement stone decreases linearly with the increase of temperature. When the temperature was less than 250 ℃, the cement stone expanded. However, when the temperature exceeded 250 ℃, it shrank. The maximum shrinkage ratio can be 25 × 10–6/℃ for the temperature of 500 ℃. The circumferential stress of the inner wall of cement sheath first increased rapidly, then slowly decreased to be stable. The larger the cement stone shrink ratio was, the greater the circumferential stress was. The maximum circumferential stress can exceed 10 MPa for the shrink ratio of 25 × 10–6/℃. It can be concluded that the circumferential stress appears in a tensile state under high temperature conditions, which can easily lead to the failure of the cement sheath seal. The strength of the cement stone should be considered when designing the cement slurry property. In addition to the decay performance, the expansion of the cement stone should also be designed to ensure that the cement stone does not shrink when subjected to high temperature conditions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cements

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Trend Analysis for Calibrated Active System Volume and differential Flow Significantly reduces False Positive Kick Alarm during drilling

Trend Analysis for Calibrated Active System Volume and Diffe...

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2024 SPE Asia Pacific Oil and Gas Conference and Exhibition, APOGCE 2024

作者： ding, danhong Mei, Yunyi Ge, Su Yong, Fengwei Lu, Yaozhong Ge, Yunhua CNPC National Elite Institute of Engineering Beijing China CNPC Engineering Technology R&D Company limited Beijing China CNPC Research Institute of Petroleum Exploration and Development Beijing China Sino Science & Technology Company Limited Israel

ISBN: (纸本)9781959025269

rapid kick detection is an essential part of rig safety. Identifying potential kick events in time is valuable and is an urgent and critical task for rig personnel and remote Operation Support Center(OSC) users. A new monitoring system has been developed by firstly calibrating the active system volume for pipe and cuttings displacement during drilling and then by detecting a statistically significant trend in the observed data rather than to rely solely on absolute values and threshold crossing to maximize the sensitivity whilst minimizing the number of false alarms. More than hundreds of historical kick alarms were reviewed and the corresponding mud logging data before the events occurred were displayed in log format against time for clear identification of anomalies in three different tracks: one track for pit volume, one for flow-in and flow-out, the third hole depth, bit depth and block position. By applying an automated rule-based system, the states of rig activities are also displayed simultaneously by detection of bit movement, pump, rotation status and other elements. It is noticed that the data absolute value, data noise, and rig operations such as sudden string movements and flow transients has significant interference to the detection of kick event and that the differential flow is more sensitive early kick indicator than pit volume in most of the historical cases. A pit volume calibrated for drill pipe and cuttings displacement during drilling and a trend analysis by applying Page-Hinkley method for monitoring both active system volumes and differential flows are established and the monitoring system is updated. The system has been tested and refined with the data flows of the historical cases in labs to maximize the sensitivity whilst minimizing the number of false alarms. A significant reduction of false positive alarms is achieved by reducing triggering of 1-2 alarms per well per week while maintaining a 100% true positive identification rate by compa

关键词： drill pipe

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WIME Systematic Innovation Method based on 6WHI and Total Factor Matrix Analysis

WIME Systematic Innovation Method based on 6WHI and Total Fa...

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2023 International Conference on Electronic, Electrical and Information technology, EEIT 2023

作者： Li, Xianing Hou, Bing Zhang, Jiqun Xiao, Yanling Liu, Lian Mi, Lan China University of Petroleum Beijing102249 China Research Institute of Petroleum Exploration & Development Beijing100083 China Artificial Intelligence Technology R&D Center for Exploration and Development CNPC Beijing100083 China Northeast Petroleum University Daqing163318 China

The involved object of systematic innovation and management is neither a single goal nor a single meth-od. Firstly, the research object is a systematic and organic whole composed of multiple node elements with a certain degree of correlation. Secondly, the research method is multi-dimensional, comprehensive, all round and highly efficient. Innovation should break through the existing thinking framework, change the existing structure, add new components, give new energy and produce new functions. The 5W1H is a questioning approach and a problem-solving method that answers all the basic elements within a problem which are what, who, when, where, why, and how. It aims to view ideas from various perspectives and gain an in-depth understanding of a specific situation. On the basis of 5W1H analysis method, this paper puts forward the 6WHI systematic innovation management method, which increases the query words weather and if of the innovation expansion solution, increases the number of questions from 6 to 8, and expands innovative forward-looking and innovative solutions diversity, with smoother pronunciation, more exciting storm. Furthermore, a systematic innovation method based on 6WHI and total factor analysis is established, and a more general and normative model WIME method is presented. This method can be utilized as a continuous process-improvement technique in an organization. Taking the 17 letters of "if question patents"as the prefix, they are just 17 common key elements in system management and innovation. For each element mentioned above, 8 questions and answers of 6WHI are given to realize systematic management and innovation. The above two types of work are arranged according to the matrix format, and then the weighted evaluation method is introduced to evaluate the above management and innovation work, so as to give a general and standardized systematic management and innovation (WIME) method. © Published under licence by IOP Publishing Ltd.

关键词： Factor analysis

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Intelligent Prediction technology for Production of Tight Oil Based on data Analysis 13th

Intelligent Prediction Technology for Production of Tight Oi...

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13th International Field Exploration and development Conference, IFEdC 2023

作者： Li, Ning Wu, Xiang-Hong Li, Xin Wang, Zhi-Ping Wang, Yue-Zhong Zhao, Li-Ao ren, Liang Wang, Hong-Liang Tian, Hong-Yu ren, Shu-Hang Jiang, Si-rui Research Center of Artificial Intelligence Research Institute of Petroleum Exploration and Development PetroChina Beijing China Artificial Intelligence Technology R&D Center for Exploration and Development CNPC Beijing100083 China Department of Asia-Pacific E&P Research Institute of Petroleum Exploration and Development PetroChina Beijing China

ISBN: (纸本)9789819702718

China is rich in tight oil resources, with a wide distribution range and a large amount of resources, making it one of the key areas for strategic replacement of future oil reserves and production. In response to issues such as strong heterogeneity of terrestrial tight oil reservoirs, difficulty in drilling high-quality oil layers, large production differences, and unclear main control factors for production capacity, a detailed analysis of dynamic and static data of production wells was conducted to analyze production performance and decline patterns. Production wells were classified according to production characteristics, and development indicators at different stages were statistically analyzed based on actual production days. Using a combination of principal component analysis and Pearson correlation coefficient, based on multiple dynamic and static data such as geological factors, fracturing factors, and development factors, and analyzing the correlation between different single and combined factors and cumulative oil production at different stages, the main control factors for different production stages of tight oil were obtained. A production capacity prediction model for tight oil fracturing horizontal wells was established based on machine learning intelligent algorithms, A production capacity evaluation and prediction technology for tight oil fracturing horizontal wells has been developed. By comparing with actual production data, the accuracy of the predicted results can meet production needs, providing a strong technical foundation for precise prediction and guidance of tight oil production in China. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Quality control

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An Efficient Fully Automated detection of Mucormycosis Using Three-dimensional deep Learning on Computer Tomography Studies

An Efficient Fully Automated Detection of Mucormycosis Using...

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2023 International Conference on recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence, rAEEUCCI 2023

作者： Shivaanivarsha, N. Kavipriya, P. Shyamkumar, M. Sathyabama Institute of Science and Technology Department of Ece Chennai India Sri Sairam Engineering College Chennai India R&d Executive Research & Development Vision Chennai India

ISBN: (纸本)9798350337426

In recent days, many people die of pulmonary embolism (PE) complications, respiratory problems that form in the deep lung. Covid-19 is the leading cause of preventable hospital death for trauma patients and despite 0.1% of the population receiving a new diagnosis annually. developing computer-aided detection (CAd) systems would alleviate these concerns;however, current systems classify computed tomography (CT) slices individually and yield many false positives from Covid-19. We have done a retrospective study on a dataset collected from various health central hospitals. There is a continued need for tools that can predict Covid and black fungal in hospitalized patients. It affects an estimated 3000-6000 Individuals just in recent days. This can cause considerable morbidity and mortality. For segmentation and classification, we mortality. For segmentation and classification, we use a 2d dense-Net. By developing more effective detection algorithms, we hope to ensure a more frequent and accurate diagnosis of covid, thereby reducing its high mortality rate. reports have shown that black fungus is steadily increasing in India as well as the death toll it causes. It has been called 'a pandemic within the Covid-19 pandemic' by medical specialists. Black fungus, or Mucormycosis, is a complication caused by a fungal infection. In India Mucormycosis has been detected in Karnataka, Uttarakhand, Telangana, Madhya Pradesh, Andhra Pradesh, Haryana, and Bihar, Primarily, fungal spores floating in the environment gives people this infection. This spreads through contact. The fungi sticks to a body part and travels inside through the nose, lungs or sinus. © 2023 IEEE.

关键词： Fungi

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Advanced 4d drilling dynamics Model Simulates downhole Vibration and Helps to Optimize in Preventing drill String Failure

Advanced 4D Drilling Dynamics Model Simulates Downhole Vibra...

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2024 SPE Asia Pacific Oil and Gas Conference and Exhibition, APOGCE 2024

作者： Zhang, Jiawei Wang, Qing du, Shiliang Zhuo, Lubin Liu, Wei Ling, Bo CNPC Engineering Technology R&D Company Limited Beijing China China National Oil and Gas Exploration and Development Company Limited Beijing China Drilling and Production Technology Research Institute PetroChina Qinghai Oilfield Company Gansu Dunhuang China

ISBN: (纸本)9781959025269

downhole vibration, such as backward or chaotic whirling, is one of the primary causes for drill string failure during drilling operation. Understanding drilling dynamics is crucial for determining the mechanism of vibration and fatigue accumulation so as to mitigate risk of drill string failure. drilling dynamics or vibration data can either be obtained from real-time measurement or simulation based on dynamics model, which plays a crucial role for drilling optimization in pre-drill planning phase. An advanced 4d drilling dynamics model, which considers the interaction between drill bit and formation, impact and friction between drill string and wellbore, constraints exerted on drill string and drill bit, is proposed to simulate the distribution and variation of 3d displacement, velocity, acceleration as well as the stress state of entire drill string within specified time period. This time domain model allows exploration of the full range of dynamics response under different drilling scenarios, which helps to optimize the performance and reliability of BHA as well as WOB/rPM selection. Moreover, drill string fatigue life prediction can also be achieved by combing simulated stress state and fatigue accumulation theory. Simulation shows that BHA with smaller- sized drill collar or fewer stabilizers are more susceptible to backward and even chaotic whirling while drilling. Also, inappropriate WOB/rPM combinations such as low WOB with high rPM could also cause the onset of severe lateral vibration. High frequency bending stress, mainly concentrated on BHA and caused by lateral vibration, is the main reason for rapid fatigue accumulation and continuous severe vibration could even result in drill string fatigue failure within hours. These findings helped to justify the 5 consecutive BHA failure and 1 washout while drilling the 171/2" wellbore with 7621 ft length of an ultra-deep well. Simulation also showed that downhole lateral vibration severity was significantly redu

关键词： drill collars

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EMI Noise Analysis Using Frequency domain Simulation Considering dynamic Semiconductor Characteristics in Flyback Converter Circuits

EMI Noise Analysis Using Frequency Domain Simulation Conside...

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Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC)

作者： Taiki Kai Tatsuki Kashihara Koji Kobayashi R&D Center Electronic Technology Development Unit Sanden Corporation Isesaki-City Japan

ISBN: (数字)9784885523472

ISBN: (纸本)9798350349498

We propose a hybrid analysis method that uses a general SPICE simulator to perform high-speed and high-precision conduction noise analysis of flyback converter circuits. Time domain analysis, generally used for conducted noise analyses, is disadvantaged by its long analysis time. Frequency domain analysis, which requires a shorter analysis time, is also used for conducted noise analyses, but it struggles to reproduce the operating characteristics of semiconductors. The hybrid analysis method enables frequency domain analysis that considers semiconductor operating characteristics by using the results of a time domain analysis as a noise source. The results of our proposed hybrid analysis method matched the results of a time domain analysis across the entire analyzed bandwidth, from $1-100 \mathrm{MHz}$. The analysis time was about $1/10$ of that of the time domain analysis.

关键词： Buck converters Frequency-domain analysis Noise Circuits Layout Electromagnetic interference Electromagnetic compatibility

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Accelerating deep Neural Networks with a Low-Cost Lossless Compression

Accelerating Deep Neural Networks with a Low-Cost Lossless C...

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2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Kim, Seongwook Byeon, Gwangeun Lee, Seungeui Bae, Youngseok Hong, Seokin Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of Advanced R&D Center Hanwha Systems Co. Ltd. Korea Republic of Agency for Defense Development Emerging Science and Technology Directorate Korea Republic of

ISBN: (纸本)9798331510756

Since deep learning inference involves a significant amount of computations, there have been a lot of efforts to accelerate the inference process by eliminating ineffectual compu-tations. As a solution to this problem, several sparsity-aware deep learning accelerators have been proposed. These accelerators perform the inference on compressed data (filters and feature maps) and dynamically remove the ineffectual multiplications with zero operands. For efficiently handling the compressed data on the accelerators, a simple and effective compression scheme, which encodes the whole data with its nonzero values and their positions, is necessary. However, prior approaches have several shortcomings, such as low compression efficiency and high complexity in compression and decompression hardware. This paper proposes a low-cost compression scheme that can be applied to sparsity-aware deep-learning accelerators. The compression scheme synergistically combines two low-cost compression schemes: Zero-Value Compression (ZVC) and Base-delta-Immediate Compression (BdI). Our experimental evaluation shows that the proposed compression scheme achieves an average compression ratio of 2.26, resulting in 2.33x performance improvement, © 2025 IEEE.

关键词： data handling

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WhaleOptNB: A Method for Automated Biomedical Text document Classification 7th

WhaleOptNB: A Method for Automated Biomedical Text Document ...

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Kumar, S. Vishnu Chohan, Jasgurpreet Singh Kalita, Kanak Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi600062 India Department of Mechanical Engineering and University Centre for Research & Development Chandigarh University Mohali140413 India Department of Mechanical Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi600062 India Jadara University Research Center Jadara University Irbid Jordan

ISBN: (纸本)9783031733239

In recent years, there has been a meteoric rise in the amount of digital information stored in the biomedical industry due to the rapid growth of the internet and other information technologies. Automated biomedical text classification has become an effective and robust method of accessing the increased amount of technical and medical literature in the biomedical sector through the classification of multiple source documents while preserving the significantly informative data to manage the enormous amount of biomedical data currently available. This is accomplished by automating the classification of multiple source documents in the biomedical field. Therefore, multi-document biomedical text classification plays an essential role in resolving the problem of gaining access to accurate and up-to-date information. A Whale Optimization Algorithm-based Weighted Naive Bayes Classifier (WhaleOptNB) for text document classification is proposed. A biomedical text document dataset is collected and preprocessed. Then, the preprocessed data's features are extracted using the Term Frequency-Inverse document Frequency (TF-IdF). To classify the biomedical text document, WhaleOptNB is utilized. To prove the efficiency of the proposed methodology, it is compared with existing methods. Simulation results show that the proposed method outperforms conventional methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Inverse problems

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